Garnering Interest on Potential Listing in a Photo or Video

ABSTRACT

Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller&#39;s experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/886,182, filed Feb. 1, 2018, entitled “Garnering Interest onPotential Listing in a Photo or Video”, the disclosure of which isincorporated by reference in this application in its entirety.

BACKGROUND

E-commerce marketplaces have struggled to improve experiences for bothbuyers and sellers of products. Typically, when a seller wishes to lista product for sale, they are required to perform a great deal of manualwork in order to formulate a “listing” for the product they wish tosell. A “listing” typically includes a picture of the product for sale,along with the price and various other parameters, such as a descriptionand the like. For example, oftentimes sellers have to perform manualresearch to find comparably-priced products so they can set acompetitive price. This may involve not only searching forcomparably-priced products on e-commerce sites, but also accessing andreviewing data describing buying and selling trends, consumer productpreference criteria, and demand forecasts which can include both textualand graphics data such as various charts, and the like. The manualresearch may also require the seller to visit various websites to seekout information about the product they wish to sell. After performingthis manual research, the seller must then ultimately construct theirproduct listing and list their product on an e-commerce website.

Needless to say, this process is extremely manually-intensive, onerous,and for sellers who are unfamiliar or unacquainted with e-commerceenvironments, can constitute a formidable barrier to entry. Furthermore,if the seller has many items to sell, he or she must perform thisprocess for each and every product they wish to list.

SUMMARY

Techniques for garnering interest on a potential product listing in adigital image, such as a photo or video, are described. In one or moreimplementations, a digital image may include one or more items that areto be sold by a seller on, for example, an e-commerce website or throughsome other network-based purchase experience. The digital image is usedto promote an on-line interaction experience with a potential buyer inwhich an item or items can be identified that appear to be of interestto the buyer. Once an item is identified, metadata associated with theidentified item can be automatically developed and used to automaticallycreate a sales listing for the item to facilitate sale of the item. Thesales listing can then be automatically listed on a website, such as ane-commerce website, to enable electronic perusal of the sales listingvia a network.

This Summary introduces a selection of concepts in a simplified formthat are further described below in the Detailed Description. As such,this Summary is not intended to identify essential features of theclaimed subject matter, nor is it intended to be used as an aid indetermining the scope of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is described with reference to the accompanyingfigures. Entities represented in the figures may be indicative of one ormore entities and thus reference may be made interchangeably to singleor plural forms of the entities in the discussion.

FIG. 1 is an illustration of an environment in an example implementationthat is operable to employ sales listing techniques described herein.

FIG. 2 depicts a system in an example implementation showing operationof a sales listing creation module of FIG. 1 in greater detail.

FIG. 3 is a flow diagram that describes operations in a sales listingcreation method in accordance with one or more implementations.

FIG. 4 depicts an example online interaction experience in accordancewith one or more implementations.

FIG. 5 is a flow diagram that describes operations in a sales listingcreation method in accordance with one or more implementations.

FIG. 6 illustrates an example user interface in accordance with one ormore implementations.

FIG. 7 illustrates an example user interface in accordance with one ormore implementations.

FIG. 8 illustrates an example user interface in accordance with one ormore implementations.

FIG. 9 illustrates an example user interface in accordance with one ormore implementations.

FIG. 10 illustrates an example user interface in accordance with one ormore implementations.

FIG. 11 illustrates an example user interface in accordance with one ormore implementations.

FIG. 12 is a flow diagram that describes operations in a sales listingcreation method in accordance with one or more implementations.

FIG. 13 illustrates an example system including various components of anexample device that can be implemented as any type of computing deviceas described and/or utilize with reference to FIGS. 1-12 to implementembodiments of the techniques described herein.

DETAILED DESCRIPTION

Overview

Techniques for garnering interest on a potential product listing in adigital image, such as a photo or video, are described. In one or moreembodiments, a digital image may include one or more items that are tobe sold by a seller on, for example, an e-commerce website or throughsome other network-based purchase experience. The digital image canreside in the form of a photo, video, a still frame captured from avideo, and the like. The digital image is used to promote an on-lineinteraction experience with a potential buyer in which an item or itemscan be identified that appear to be of interest to the potential buyer.Various different types of interaction experiences can be promoted usingthe digital image. For example, one such interaction experience caninclude a social interaction between the seller and the potential buyer.The social interaction can include, by way of example and notlimitation, a textual chat session, an on-line voice conversation, apeer-to-peer conversation, and the like. Another such interactionexperience can include the manner in which the potential buyer interactswith the digital image. For example, when presented with a digitalimage, a potential buyer may zoom in on a particular item of interest.Alternately or additionally, the potential buyer may zoom in on a regionof the digital image that includes multiple items.

Once an item(s) is identified, metadata associated with the identifieditem can be automatically developed and used to automatically create asales listing for the item to facilitate sale of the item. In variousimplementations, the sales listing can be the first initial saleslisting for an item, where a sales listing for that item did notpreviously exist. The metadata can be developed in a variety ofdifferent ways, examples of which are provided below. The sales listingcan then be automatically listed on a website, such as an e-commercewebsite, to enable electronic perusal of the sales listing via anetwork. In addition, in various implementations, the sales listing canbe listed on multiple different platforms, systems, and sites. Whetherlisted on a single website or multiple different websites, the saleslisting can be continuously updated automatically, based on buyerinteractions with the sales listing and/or the digital image from whichthe sales listing was created. For example, in an instance where thesales listing is listed on multiple different websites, when a buyerinteraction causes a modification of the sales listing, thatmodification can be communicated by the particular web site on which theinteraction occurred, or through an intermediary such as a monitoringbot, to the other websites either directly or indirectly so that thesales listing can remain synchronized across the multiple websites.

Thus, various implementations are able to leverage the interaction fromone or more potential buyers relative to a digital image toautomatically create and update a sales listing for items that appear tobe of interest to the buyers. This reduces or eliminates, all together,the manual effort previously required of sellers in researching andcollecting data on each item they wish to sell. Because of the technicalnature of the innovative solutions described herein, the solutions arereadily and quickly scalable which, in turn, greatly improves theseller's experience. Thus, the solutions can transform computing devicesinto powerful mechanisms to facilitate the exchange of items and money.

For example, a seller may have a large number of items they wish tosell. In the past, the seller would be required to manually researcheach and every item in order to intelligently prepare an informed saleslisting. Now, through the innovative solutions described herein, aseller may simply take one photograph or make one video that includesall of the items for sale. Based on buyer interaction experiences, saleslistings for each item for sale can be automatically created and listed.

As such, the described innovations improve upon the currentstate-of-the-art for a number of different reasons. For example, thedescribed innovations are extremely helpful and very apt for casualsellers who may not necessarily be comfortable in, or knowledgeableabout identifying items that they can sell. The technical solutionsdescribed herein automatically take care of all of the details for thesetypes of sellers. In addition, because of the technical nature of theinnovations, for sellers who do not have the time to manage and list allof the items they wish to sell, the innovative solutions provide a“one-stop” process in which a single digital image can serve as thestarting point for an automatically-created, automatically-listed saleslisting for one or more items. Accordingly, no longer are potentialsellers required to manually search for comparably-priced products one-commerce sites, access and review data describing buying and sellingtrends, consumer product preference criteria, and demand forecasts.Potential sellers are also relieved of the burden of visiting variouswebsites to seek out information about the product they wish to sell.The innovative technical solutions thus emphasize and promote speed,efficiency, and ease of usability for sellers in an e-commerce setting.

In the following discussion, an example environment is first describedthat may employ the techniques described herein. Example procedures andsystems are also described and shown as blocks which may be performed inthe example environment as well as other environments. Consequently,performance of the example procedures is not limited to the exampleenvironment and systems and the example environment and systems are notlimited to performance of the example procedures.

Example Environment

FIG. 1 is an illustration of a digital medium environment 100 in anexample implementation that is operable to employ techniques to garnerinterest on a potential listing in a photo or video described herein.The illustrated environment 100 includes a computing device 102 that iscommunicatively coupled to a service provider system 104 via a network106. Computing devices that implement the computing device 102 and theservice provider system 104 may be configured in a variety of ways.

A computing device, for instance, may be configured as a desktopcomputer, a laptop computer, a mobile device (e.g., assuming a handheldconfiguration such as a tablet or mobile phone), configured to be worn(e.g., as goggles) and so forth. Thus, a computing device may range fromfull resource devices with substantial memory and processor resources(e.g., personal computers, game consoles) to a low-resource device withlimited memory and/or processing resources (e.g., mobile devices).Additionally, although a single computing device is shown, a computingdevice may be representative of a plurality of different devices, suchas multiple servers utilized by a business to perform operations “overthe cloud” for the service provider system 104 as described in FIG. 13.

The computing device 102 is illustrated as being held by a user 108 in aphysical environment, e.g., a living room 110. The computing device 102includes a digital camera 112 that is configured to capture digitalimages 114 of an outside physical environment (e.g., the living room110), such as through use of a charge coupled device (CCD) sensor orvideo camera. The captured digital images 114 may then be stored in acomputer-readable storage medium and/or rendered for display by adisplay device, e.g., LCD, OLED, LED, etc. The digital image or imagesmay include one or more items, such as the illustrated coffee table, andcup and pitcher resting on the coffee table that are to be sold by theuser 108 which, in this case, is the “seller”.

The computing device 102 also includes, in at least someimplementations, a sales listing creation module 116 that is configuredto process digital image 114 using item inventory manager module 120, toidentify one or more items that are to be sold by a seller on, forexample, an e-commerce website or through some other network-basedpurchase experience. In some implementations, the sales listing creationmodule 116 includes an interaction monitoring module 121 that monitorsinteraction experiences associated with a particular item or items. Asnoted above, various different types of interaction experiences can bemonitored. For example, one such interaction experience can include asocial interaction between the seller and a potential buyer. Alternatelyor additionally, another such interaction can include the manner inwhich a potential buyer interacts with digital image 114.

The sales listing creation module 116 is configured to use informationascertained from item inventory manager module 120 and interactionmonitoring module 121 to automatically create a sales listing 122 thatcan be used to sell the item or items on the E-commerce website, asdescribed in more detail below. Alternately or additionally, aspects ofthe sales listing creation module 116 can be implemented by a thirdparty, such as by the service system provider 104. In someimplementations, aspects of the sales listing creation module 116 can bedistributed between computing device 102 and service provider system104. That is, in some instances some modules that contribute to thecreation of sales listing 122 may reside on a computing device 102,while other modules may reside on the service provider system 104. Forease of description, however, the modules are shown as residing oncomputing device 102.

The item inventory manager module 120 is representative of functionalityto manage an inventory of items. This includes items that are owned bythe user 108 that the user wishes to sell. In one or moreimplementations, the item inventory manager module 120 is configured tocollect or otherwise analyze digital images 114. This may includedigital images 114 of physical items in the living room 110 in thisexample, or digital images captured of physical photos of items the userwishes to sell. The digital image 114 may also be captured from a userinterface output by the computing device 102, e.g., as a screenshot froma frame buffer provided by an application, an example of which isprovided below.

In one or more implementations, the item inventory manager module 120includes item recognition functionality to recognize items includedwithin the digital image 114, e.g., via machine learning. Broadly,“machine learning” refers to a field of computer science that givescomputers the ability to learn without being explicitly programmed. Manydifferent types of machine learning can be utilized in variousimplementations, as will be appreciated by the skilled artisan.

Machine learning tasks are typically classified into two broadcategories, depending on whether there is a learning “signal” or“feedback” available to a learning system. The first category isreferred to as “supervised learning”, and the second category isreferred to as “unsupervised learning.”

In supervised learning, the computer is presented with example inputsand their desired outputs, given by a “teacher”. The goal is to learn ageneral rule that maps inputs to outputs. As special cases, the inputsignal can be only partially available, or restricted to specialfeedback. The special feedback can include semi-supervised learning,active learning, and reinforcement learning. In unsupervised learning,no labels are given to the learning algorithm, leaving it on its own tofind structure in its input. Unsupervised learning can be a goal initself, e.g., discovering hidden patterns in data, or a means towards anend, e.g., feature learning.

Another categorization of machine learning tasks arises when oneconsiders the desired output of a machine-learned system. This caninclude such things as classification, regression, clustering, densityestimation, and dimensionality reduction. Needless to say, numerousdifferent machine learning techniques can be employed by the iteminventory manager module 120 to recognize items that appear in digitalimage 114.

From its machine learning analysis and item recognition of the digitalimage 114, the item inventory manager module 120 may collect datapertaining to this recognition, as well as other information, such asinformation developed by interaction monitoring module 121. In one ormore implementations, this data and other information can be used toautomatically create a sales listing 122 for the item. A typical saleslisting will include an image of the item and the item price. Otherinformation may be included as well such as, by way of example and notlimitation, an item description, item condition, packaging, itemwatchers, feedback, trending price, delivery expectation, warrantyinformation, and the like.

In one or more implementations, the sales listing creation module 116includes functionality, e.g., the interaction monitoring module 121, tomonitor a social interaction between the user (seller) and one or morepotential buyers. From this monitored social interaction, the iteminventory manager module 120 is then able to identify items for sale andcollect data pertaining to the identified data in order to automaticallycreate sales listing 121.

Alternately or additionally, in one or more implementations, datadescribing the recognized items, for instance, may be communicated viathe network 106 to the service provider system 104. The service providersystem 104 may include a sales listing creation module 116 that isconfigured to obtain data related to the items (e.g., through use of asearch) from a storage device 124 or from other sources such as otherE-commerce websites, various webpages, and the like. This data may thenbe communicated back to the computing device 102 via the network 106 foruse by the item inventory manager module 120 in automatically creatingthe sales listing 122. Alternately or additionally, the service providersystem 104 may automatically create the sales listing, thus relievingthe computing device 102 from having to create and list the saleslisting.

In general, functionality, features, and concepts described in relationto the examples above and below may be employed in the context of theexample procedures described in this section. Further, functionality,features, and concepts described in relation to different figures andexamples in this document may be interchanged among one another and arenot limited to implementation in the context of a particular figure orprocedure. Moreover, blocks associated with different representativeprocedures and corresponding figures herein may be applied togetherand/or combined in different ways. Thus, individual functionality,features, and concepts described in relation to different exampleenvironments, devices, components, figures, and procedures herein may beused in any suitable combinations and are not limited to the particularcombinations represented by the enumerated examples in this description.

Sales Listing Creation

FIG. 2 depicts a system 200 in an example implementation showingoperation of the sales listing creation module 116 of FIG. 1 in greaterdetail. The following discussion describes techniques that may beimplemented utilizing the previously described systems and devices.Aspects of the procedure as shown stepwise by the modules of FIG. 2 maybe implemented in hardware, firmware, software, or a combinationthereof. The procedure is shown as a set of blocks that specifyoperations performed by one or more devices and are not necessarilylimited to the orders shown for performing the operations by therespective blocks.

To begin, a digital image 114 is obtained by the digital camera 112. Thedigital image 114, for instance, may be captured using a digital camera,as a screenshot captured from a frame buffer of the computing device102, a digital picture of one or more items, and so forth.

The digital image 114 is then processing by a sales listing creationmodule 116 to automatically create a sales listing 122. The saleslisting creation module 116 may reside on the computing device 102,service provider system 104, or have aspects of its functionalitydistributed between computing device 102 and service provider system104.

The item inventory manager module 120 includes an item recognitionmodule 202 configured to recognize an item within the digital image 114.The item recognition module 202, for instance, may employ a machinelearning module 204 configured to employ models 206 usable to recognizethe item using machine learning, e.g., neural networks, convolutionalneural networks, deep learning networks, structured vector machines,decision trees, and so forth. The models 206, for instance, may betrained using training digital images that are tagged with correspondingidentifications. In an implementation, these training digital images andtags are obtained from a commerce service provider system that aretagged by sellers using the system. As a result, a multitude ofaccurately tagged training digital images may be obtained with minimalcomputation and user cost as opposed to conventional manual taggingtechniques. Although illustrated as implemented locally by the computingdevice 102, as noted above, this functionality may also be implementedin whole or in part by a service provider system 104 via the network106.

Thus, the item recognition data 208 describes an item included in thedigital image 114. An item data collection module 210 is then employedto collect item metadata 212 that pertains to the recognized item. Thismay be performed locally through a search of a local storage deviceand/or remotely through interaction with a sales listing creation module116 of a service provider system 104 via a network 106.

Alternately or additionally, in at least some implementations, aninteraction monitoring module 121 also develops data which can be usedto enable the item data collection module 210 to collect item metadatato be used in the sales listing 122. That is, as noted above, thedigital image is used to promote an on-line interaction experience witha potential buyer in which an item or items can be identified thatappear to be of interest to the potential buyer. Various different typesof interaction experiences can be promoted using the digital image, andthe interaction monitoring module 121 can be configured to monitor eachor any different type of interaction experience. For example, one suchinteraction experience can include a social interaction between theseller and the potential buyer. The social interaction can include, byway of example and not limitation, a textual chat session, an on-linevoice conversation, a peer-to-peer conversation, and the like. Duringthe social interaction, the interaction monitoring module can monitorthe conversation for contextual data, such as keywords, the use ofemojis, and the like, to enable the item data collection module 210 todevelop item metadata. Another such interaction experience can includethe manner in which the potential buyer interacts with the digitalimage. For example, when presented with a digital image, a potentialbuyer may zoom in on a particular item of interest. Alternately oradditionally, the potential buyer may zoom in on a region of the digitalimage that includes one or more items. In this instance, the interactionmonitoring module 121 can monitor the buyer's interaction with thedigital image. This can take place using various techniques. Forexample, as a buyer interacts with a digital image, data describing theinteraction such as a “zoom” action can be produced. From this data, theinteraction monitoring module 121 can ascertain that a buyer has zoomedin on a particular item or region of a digital image. From there, theitem or region can be isolated and analyzed in more detail to enable theitem data collection module 210 to develop the item metadata 212.

A variety of different types of item metadata 212 may be obtained from avariety of different types of service provider systems 104. In oneexample, the service provider system 104 provides information relatingto purchase or sale of the item, e.g., product name, productdescription, price for purchase or sale (e.g., based on onlineauctions), and so forth. In another example, the service provider system104 provides information relating to customer reviews of the product,e.g., a number of “stars” or other rating, textual reviews, and soforth.

The item metadata 212 in this example is then processed by the iteminventory manager module 122 to automatically create a sales listing 122for the item to facilitate sale of the item. The sales listing can thenbe automatically listed on an E-commerce website 214.

Accordingly, the various implementations described above and below areable to leverage the interaction from one or more potential buyersrelative to a digital image to automatically create a sales listing foritems that appear to be of interest to buyers. This reduces oreliminates the manual effort previously required of sellers inresearching and collecting data on each item they wish to sell.

Having considered an example system in accordance with one or moreimplementations, consider now an example method in accordance with oneor more implementations.

FIG. 3 is a flow diagram that describes operations in accordance withone or more implementations. The operations can be performed inconnection with any suitable hardware, software, firmware, orcombination thereof. In at least some implementations, the operationscan be implemented by a system, such as those systems described aboveand below.

At block 300, a digital image is used to promote an on-line interactionexperience with a potential buyer in which an item or items appearing inthe digital image can be identified to be of interest to the potentialbuyer. The on-line interaction experience is associated with the digitalimage and can include, by way of example and not limitation, a buyer'sinteraction with the digital image itself, a social interaction betweenthe buyer and the seller, and the like. This operation can be performedin any suitable way. For example, this operation can be performed bycausing the digital image to be presented on a computing deviceassociated with the potential buyer. For example, a service providersystem 104 may maintain a website in which digital images have beenuploaded by various sellers. The potential buyer may then navigate tothe website and select a particular digital image for electronicperusal. Alternately or additionally, a potential seller may transmit,or have transmitted on their behalf, a digital image to a potentialbuyer during the course of a social interaction. In at least someimplementations, the on-line interaction experience is used toautomatically create a sales listing for the item or items, where asales listing did not previously exist for the item or items. That is,the on-line interaction experience is used to automatically create aninitial sales listing for item that is to be sold. At block 302, theon-line interaction experience with the potential buyer is monitored.This operation can be performed in any suitable way, examples of whichare provided above and below.

At block 304, data associated with the online interaction experiencewith potential buyer is processed, effective to develop metadataassociated with the item or items of interest. Examples of such metadataare provided above and below. At block 306, the developed metadata isused to automatically create a sales listing for the item or items ofinterest. The sales listing is designed to facilitate sale of the itemsor items of interest on an E-commerce website. Again, in one or moreimplementations, the sales listing that is automatically created is aninitial sales listing, where one did not previously exist for the itemor items.

At block 308, the sales listing is caused to be automatically listed onthe E-commerce website. Doing so effectively enables electronic perusalof the sales listing via a network.

The automatic method described above greatly reduces the extent to whicha seller must manually research and develop their own particular saleslisting. In doing so, the innovative solutions provide a highlyscalable, effective, fast, and efficient approach to bringing buyers andsellers together.

Having considered the above-described systems and methods, consider nowtwo implementation examples that draw upon the principles justdescribed. The first example pertains to leveraging a buyer'sinteraction with a digital image itself, to automatically create thesales listing. The second example pertains to enabling sales of itemsappearing in a digital image based upon interaction between the sellerand one or more potential buyers.

Leveraging a Buyer's Interaction with a Digital Image to AutomaticallyCreate the Sales Listing

FIG. 4 depicts an example implementation 400 of user interaction, e.g.an online interaction experience, with a digital image that has beencaptured as described above. In this particular example, a digital imagehas been taken of the coffee table appearing in FIG. 1 and the itemsappearing on the coffee table. This implementation 400 is illustratedusing first, second, and third stages 402, 404, 406.

At the first stage 402, a user interface 408 is output by the computingdevice 102, e.g., by way of a touchscreen display device. The userinterface 408 may be configured as a “live feed” of digital images 114obtained in real time from the digital camera 112 in this example.

At the first stage 402, the user, in this case a potential buyer, hasselected the digital image that contains the coffee table and the itemsappearing thereon.

At the second stage 404, a user input is received that selects an itemdisplayed in the user interface 408. This selection can be conveyed to aservice provider system by way of a suitable API call into the serviceprovider system. In this particular case, the user has zoomed up on thedigital image by way of a zoom operation. In the illustrated example,the user input is detected as a tap of a finger of the user's hand 418that is detected using touchscreen functionality of the computingdevice. The touchscreen functionality, or any other suitable input,generates data associated with one or more potential buyer interactionswith the digital image. In this way, a user may distinguish betweenmultiple items displayed concurrently in the user interface 408. Otherexamples may also be used, such as a spoken utterance or other gestures.In addition, a potential buyer need not select only one item. Rather,the potential buyer may zoom the digital image such that multipledifferent items appear in a region of the image.

In response to the user selection of the second stage 404, the digitalimage 114 or, more accurately, the data associated with the potentialbuyer interactions, is then processed by the item recognition module 202at the service provider system, as described above, to identify the item(e.g., the pitcher in the illustrated example) as item recognition data208. The item recognition module 202 can also process the dataassociated with the potential buyer interactions to define at least oneregion of interest containing an item or items of interest. These itemsappearing in the region can then be processed by the item recognitionmodule 202 as described above, to identify the items.

The item recognition data 208 can be processed by the item inventorymanager module 120 of the service provider system to develop metadataassociated with the item or items of interest. Accordingly, the serviceprovider system 104 in this example searches a storage device 124 foritem metadata 212 that pertains to the identified item. The itemmetadata 212 is then used to automatically create a sales listing forthe item of interest to facilitate sale of the item on an E-commercewebsite.

As shown at the third stage 406, an example sales listing is shown thatincludes a picture of the item, in this case the pitcher, along with aname and price 410 (e.g., average price, price for sale, price to buy,etc.) of the item. In addition, the sales listing can include otherinformation such as that described above, e.g., a product description, alink to comparable items, suggested comparable items along withassociated prices, and the like.

FIG. 5 is a flow diagram that describes operations in accordance withone or more implementations. The operations can be performed inconnection with any suitable hardware, software, firmware, orcombination thereof. In at least some implementations, the operationscan be implemented by a system, such as those systems described aboveand below.

At block 500, data is received associated with one or more potentialbuyer interactions with a digital image. The digital image contains oneor more item images of one or more respective items that are to be soldon an e-commerce website. Any suitable type of potential buyerinteraction can generate the received data. In at least someembodiments, the interaction can comprise a touch-related input.Alternately or additionally, the interaction can be a verbal action, agesture, a natural user interface input, and the like. At block 502, thedata associated with the potential buyer interactions is processed todefine at least one region of interest containing one or more items ofinterest. For example, a potential buyer may simply zoom into a regionthat contains multiple items of interest. Alternately or additionally, apotential buyer may zoom into a region that contains only one item ofinterest. Alternately or additionally, the buyer may tap-select aparticular item appearing in a digital image.

At block 504, the item or items of interest contained within the regionare identified and, at block 506, metadata associated with the item oritems of interest is developed. Examples of how this can be done areprovided above. For example, various machine learning techniques can beutilized to identify the item or items of interest. Additionally,metadata developed therefrom can be acquired from any suitable sourcesuch as, by way of example and not limitation, the e-commerce website onwhich the sales listing is to be listed or a source other than thee-commerce website.

At block 508, the developed metadata is used to automatically create asales listing for the item of interest to facilitate sale of the item ofinterest on the e-commerce website. At block 510, the sales listing iscaused to be automatically listed on the e-commerce website. Thisoperation can be performed in a variety of different ways. For example,if the sales listing is automatically created on a computing device,such as computing device 102, the sales listing can be caused to belisted by transmitting the sales listing to the e-commerce website or arepresentative thereof. If, on the other hand, the sales listing isdeveloped by the e-commerce website or a representative thereof, thesales listing can be caused to be listed by simply taking the normalsteps that are undertaken to list a sales listing.

Having considered the above-described implementation, consider now animplementation that enables sales of items appearing in a digital imagebased upon interaction between the seller and one or more potentialbuyers.

Enabling Sales of Items Appearing in a Digital Image Based UponInteraction Between the Seller and One or More Potential Buyers

In at least some implementations, a digital image can be utilized topromote an online interaction experience in the form of a socialinteraction between the seller and one or more potential buyers. Asnoted above, the social interaction can include, by way of example andnot limitation, a textual chat session, an on-line voice conversation, apeer-to-peer conversation, and the like. As an example, consider FIG. 6.

There, a social media user interface is shown generally at 600. Anysuitable type of social media user interface can be utilized.Alternately or additionally, any suitable type of application that canenable on-line, social interaction between two or more users can beutilized. In this particular example, a user—in this case a seller—haschosen to create an “event” and, as such, an event user interface ispresented at 602. The event user interface enables the user to sign in,provide an event title, and select resources, such as an image filecontaining one or more digital images. An “event” is a construct throughwhich the seller can present items that they wish to sell and engage inan on-line interaction experience with a potential buyer in an effort tosell the items. In this particular example, the on-line experience ispromoted by way of a user interface component 604 which enables atextual chat session between two or more people. In addition, the eventenables items to be identified and, at the same time, sales listings forthe items to be automatically created and listed on one or moree-commerce websites, as described above and below.

Once the seller creates the event, he or she can upload a digital imagethat contains items that the seller wishes to sell. Any suitable type ofdigital image can be utilized including, by way of example and notlimitation, a photograph, a 360-degree photograph, a video, a frame froma video, and the like. As an example, consider FIG. 7.

There, the user has uploaded an image with on-sale items. In this case,an item 700 (WALL-E) is going to be listed for sale. At this point, theseller has not yet created his or her inventory and has not gone throughany type of selling process. Specifically, at this point in the process,a sales listing for item 700 does not exist. Rather, the seller hassimply uploaded a digital image containing one or more items that are tobe sold and for which sales listings are to be created. At this point inthe event, the seller chooses to initiate a dialogue with friends. As anexample, consider FIG. 8.

There, the seller has chosen to initiate an online interactionexperience with a friend by way of user interface component 604. In thisinstance, during the online interaction experience the potential buyerexpresses an interest in item 700 by asking “How much for the WALL-E?”.During this on-line interaction experience with the potential buyer, asystem, such as the system described above, monitors the on-lineinteraction experience and processes data associated with theinteraction experience. Monitoring the on-line interaction experiencetakes place by way of an event loop which continuously monitors theinteraction experience. This can be done through any suitable technique.In this particular example, an item inventory manager module 120 (FIG.2) can monitor the textual conversation between the seller and thepotential buyer or buyers through, for example, natural languageprocessing techniques, and can use the monitored data—in this case,keywords that are utilized in the conversation—to develop metadataassociated with the item or items of interest. The item inventorymanager module 120 can also monitor for other things such as the use ofemojis (e.g., a smiley face when a price is mentioned by the seller),and the like. Any suitable techniques can be utilized to developmetadata, examples of which are provided above. Specifically, in someimplementations, image recognition module 202 and machine learningmodule 204 can operate to develop metadata associated with the item oritems of interest. In at least some implementations, the event loopcontinuously monitors and collects product metadata including thingssuch as interest, price, condition, and the like.

In addition to identifying the item or items of interest, in at leastsome embodiments, the item of interest can be highlighted as indicatedat 800. There, a shaded, visual box has been drawn around the item todraw the participants' attention to the item currently being discussed.

During this time, the system uses the developed metadata toautomatically create a sales listing for the item or items of interestto facilitate sale of the item or items of interest on an e-commercewebsite. Once the sales listing is automatically created, the system cancause the sales listing to be automatically listed on the e-commercewebsite effective to enable perusal of the sales listing via a network.

In one or more implementations, the event loop continuously collects andupdates product status based on sale, availability, and the like. As anexample, consider FIG. 9.

There, an indication 900 indicates that the product has been sold or is“sold out”. In addition to updating the user interface to reflect thecurrent state of the sale, the sales listing can also be modified on thee-commerce website to indicate that the item has been sold.

In addition, in various implementations, conversational signalscollected by the event loop can help to identify products that are notfor sale but which appear in the image and/or can enable additionalitems to be sold and for sales listings to be created. As an example,consider FIG. 10.

There, the buyer has indicated an interest in purchasing the headphones.The event loop identifies that the seller does not wish to sell theheadphones and, accordingly, places an indicator 1000 on the item tovisually indicate that the headphones are not for sale.

FIG. 11, on the other hand, depicts a situation in which a real-timesales option can be created based on conversational cues developed bythe event loop. In this particular case, the potential buyer learns thatthe headphones are not for sale, but then inquires about the fitbit byasking “Can I buy the fitbit?”. The seller indicates their willingnessto sell the item to the potential buyer. During this conversation, theevent loop continues to develop metadata by monitoring the on-lineinteraction experience and creates a sales listing automatically. Thesystem also visually identifies the item of interest by placing a shadedbox around the item with an indicator “buy” to indicate that thehighlighted item is the current topic of discussion between the sellerand the potential buyer. The “buy” indicator can be selected by thepotential buyer in order to initiate and/or complete the buying process.

Having considered the above-described implementations, consider now anexample method in accordance with one or more implementations.

FIG. 12 is a flow diagram that describes operations in accordance withone or more implementations. The operations can be performed inconnection with any suitable hardware, software, firmware, orcombination thereof. In at least some implementations, the operationscan be implemented by a system, such as those systems described aboveand below.

At block 1200, a user interface is presented to enable a potentialseller to create an event that can be used to sell one or more itemsonline Any suitable user interface can be utilized, an example of whichis provided above. At block 1202, a digital image is received thatcontains one or more item images of one or more respective items thatare to be sold online by the potential seller as part of the event. Anysuitable type of digital image can be received, as described above. Atblock 1204, social interaction between the potential seller and one ormore potential buyers is enabled. The social interaction is regardingthe items appearing in the digital image. In at least someimplementations, the social interaction is directed to enabling thepotential seller to sell the items appearing in the digital image. Atblock 1206, the social interaction is monitored between the potentialseller and the potential buyer or buyers to extract metadata. At block1208, sale of the one or more items appearing in the digital image isenabled. This operation can be performed in any suitable way. Forexample, in at least some embodiments, the sale of items is enabled byautomatically creating a sales listing which is then automaticallylisted on an e-commerce website. Alternately or additionally, sale ofthe one or items is enabled by enabling a buyer to buy the itemappearing in the digital image. This can be performed by, for example,providing a suitable user interface element, e.g., “buy”, that isdisplayed on or near the particular item which, in turn, can be selectedby the buyer to initiate the buying process. In at least someimplementations, at block 1210, the digital image is caused to beupdated based on metadata extracted by monitoring the social interactionbetween the potential seller and the potential buyer or buyers. Updatingthe image can be performed in any suitable way. For example, in someimplementations, the digital image can be updated by displaying varioushighlights or other information on or near the item of interest. Onesuch example, described above, includes overlaying a shaded box tohighlight the item of interest. Another such example includes updatingthe digital image to indicate the state of the sale, i.e., “sold”.

Having considered the implementations described above, consider nowthree different implementation scenarios that can be utilized inaccordance with the principles described above. Each of theseimplementations scenarios can be utilized in connection with any or allof the implementations described above.

Implementation Scenarios

In the following discussion, three different implementation scenariosare described. The first implementation scenario pertains to an auctionscenario where multiple bidders can bid on an item or items of interest.The second implementation scenario pertains to user interface scenariosin which different aspects of the user interface can be modified toenhance the user's experience. The third implementation scenariopertains to details associated with scaled up viewer numbers.

Auction Scenarios

In some implementations, potential buyers may be able to drive the priceof a particular item up or down based on different parameters such asthe condition of an item, shipping requirements, the likelihood ofbuyers attempting to buy an item, buyer comments on a particular itempertaining to condition or appearance, and the like. For example, if aparticular item appears to be in poor condition, a potential buyer maycomment on that and offer a price that is below the seller's askingprice. In this instance, the interaction between the seller and thebuyer can be monitored. In this case, metadata such as the buyer's offerprice, positive or negative comments, and the like can be used toautomatically create or modify a sales listing. For example, if a saleslisting had previously been created that included the seller's askingprice, a new auction price can be listed on the sales listing toindicate the potential buyer's lower bid and to reflect any commentsmade about the item. This information can, in turn, be used by otherpotential buyers to bid the price up or down.

In some instances, auction scenarios can include both a privatecomponent and a public component that operates in parallel. For example,the private component of an auction scenario can include the onlinesocial interaction between the seller and one or more potential buyers.This might occur, for example, in a chat or social networking session,or some other online instrumentality in which information and data canbe exchanged between the seller and one or more potential buyers in aprivate or semi-private context. As described above, this informationexchange can be used to develop metadata to automatically create a saleslisting which can be automatically listed on an e-commerce website. Oncethe sales listing is automatically listed on the e-commerce website, thepublic component of the auction scenario can enable members of thegeneral public to interact with the sales listing to bid the price up ordown, offer comments on items, and the like. As such, changes to thesales listing can be dynamically updated as a function of both theprivate component in which the sales listing is adjusted based on theprivate or semi-private social interaction between the seller and thebuyer, and the public component in which buyers bid on an item withoutnecessarily socially interacting with the seller. To this extent then, aprivate component which can include a “private” or “semi-private”context, pertains to a context in which an individual or group ofindividuals, respectively, take part in an online social interactionwith the seller. A “public” pertains to a context in which an individualor group of individuals do not take part in an online social interactionwith the seller as part of the selling or auction process.

Having considered various auction scenarios, consider now user interfacescenarios that can be employed in the various implementations describedherein.

User Interface Scenarios

In one or more implementations, a user interface can be manipulated tohighlight different items based on interest in particular item. Someexamples of user interface manipulations are described above and below.

Interest in a particular item can be measured in different ways. Forexample, interest in a particular item may be measured based on buyersexpressing an interest in the item or bidding on particular items. Forexample, a buyer may interact with the seller and indicate that 15 daysto ship an item is undesirable. Based on this expressed sentiment, aninterest level may be measured that indicates that the particular itemis not as interesting to buyers as other items. In these instances,programmatic callbacks can be made to the service provider system, suchas service provider system 104 in FIG. 2, to enable the system to modifythe user interface in some manner. For example, the size of the item inthe user interface may be reduced or a tag, other icon or color-relatedsignal, sparkle, and the like, may be applied on or near the item toindicate the level of interest.

The user interface can also be manipulated based on the number of itemsthat might appear in a scene. For example, if many items appear in ascene, some of which may overlap with one another, different types ofvisual manipulations might be used. For example, for items in which ahigh level of interest is registered, those items might be digitally“cut out” and separately displayed somewhere else in the user interface.The cut out approach would work quite well in the event that the digitalimage in which the items appear is a video. In this case, the “cut out”might include a frame that is captured and cropped to select the item,and then overlaid on the video itself. For example, items of interestmay be “cut out” and displayed in a horizontal bar at the bottom of theuser interface, or a vertical bar on either the left or right side ofthe user interface. In some instances, content of the bar is pannable orscrollable to reveal items that appear in the bar. In some instances,cut out items may be placed in the bar in a hierarchical order that isassociated with the measured level of interest. For example, items thatappear to have higher levels of interest may be sorted left-to-right ortop-to-bottom, to indicate their place in a hierarchy. Alternately oradditionally, a header or a footer might be employed in connection withan item or items in which interest is measured. The header or footer maycontain information that indicates the level of interest in a particularitem through any suitable manner.

In some implementations, interest can be expressed in different ways.For example, an overall viewing community's interest in a particularitem or items can be measured. Such can occur to the use of any suitableparameters examples of which are mentioned above. Alternately oradditionally, an individual's interest in a particular item or item canbe measured. Such can occur through the use of parameters that areparticular to the individual whose interest is being measured.

For example, with respect to an overall viewing community's interest,such interest can be measured by considering parameters across theviewing community such as, by way of example and not limitation,comments made by individual viewers, number of bids placed by theviewing community as measured against a threshold, number of positive ornegative comments made by individual viewers making up the community asmeasured against a threshold, and the like. The user interface withrespect to these items can then be modified to reflect the overallviewing community's interest in an item. The same or similar approachcan be used with respect to an individual viewer's interest in items.Any visual instrumentalities used to highlight these items can then betailored to reflect whether the interest is that of the overall viewingcommunity or an individual. For example, in some instances acolor-related icon (e.g., red, yellow, or green) can be used tohighlight a particular item, along with multiple cascaded head andshoulders profiles to indicate that the interest is that of the overallviewing community. Similarly, in some instances the same or similarcolor-related icon can be used with a single head and shoulders profileto reflect the interest of an individual user. Both types of visualinstrumentalities can be displayed on, for example, the seller's userinterface so that the seller can ascertain, at a glance, whetherinterest in a particular one of their items is that of the overallviewing community or a particular individual with whom they may have anonline social interaction. For the overall viewing community, the visualinstrumentality can be displayed on their respective user interfaces onor near a particular item so that individuals in the overall viewingcommunity can likewise ascertain, at a glance, the overall communityinterest in a particular item. In the viewing community context, thismight facilitate bidding for items that appear to be popular.

In some implementations, visual instrumentalities can be used to modifythe user interface with respect to a particular item by using varyingdegrees of luminosity or color intensity to indicate interest. Forexample, for items that appear to have a high level of interest, agreater degree of “glow” or “sparkle” might be used. That is, morepopular items may glow brighter than less popular items.

Having considered the notion of user interface scenarios, consider nowthe notion of scaled up viewer numbers and how such situations can behandled.

Scaled Up Viewer Numbers

In some implementations, the number of viewers or potential buyers mayescalate or scale quickly, particularly in scenarios where the item oritems of interest has or have a high degree of interest. For example, insome instances a celebrity may wish to conduct a fundraiser and auctionoff some of their items. Once the news gets out about the celebrityauction, it is reasonable to believe that a large number of potentialbuyers may be interested in viewing the items, and this number may scalequickly.

In some implementations, scalability can be addressed by using so-calledunique endpoints. So, for example, each item of a group of items wouldbe associated with its own unique endpoint. The endpoint is identifiedby a globally unique identifier or GUID. Each unique endpoint is thenassociated with its own unique API call. As interest grows in an item,and as potential buyers interact with respect to a particular item orwith each other as described above, API calls can be made to each uniqueendpoint (using the associated GUID) which, in some implementations, canbe exposed by a service provider system, such as service provider system104 in FIG. 2. These API calls can enable the service provider system totrack, for each individual item, such things as the total number ofpotential buyers who are interested in an item, comments made about anitem, and all of the information mentioned above. Scalability ispromoted through the use of these individual APIs for each item becausethe service provider system can actively track the actual users who areactively engaged in the auction process for a particular item. Thisinformation, as it is curated and managed by the service providersystem, can then be surfaced to all interested parties through acallback mechanism. The information can also be utilized toautomatically modify any associated sales listings.

Having consider the example method described just above, consider now anexample system and device that can be utilized to implement thedescribed innovations.

Example System and Device

FIG. 13 illustrates an example system generally at 1300 that includes anexample computing device 1302 that is representative of one or morecomputing systems and/or devices that may implement the varioustechniques described herein. This is illustrated through inclusion ofthe sales listing creation module 116, aspects of which can beimplemented on computing device 1302, platform 1316, or both. Thecomputing device 1302 may be, for example, a server of a serviceprovider, a device associated with a client (e.g., a client device), anon-chip system, and/or any other suitable computing device or computingsystem.

The example computing device 1302 as illustrated includes a processingsystem 1304, one or more computer-readable media 1306, and one or moreI/O interface 1308 that are communicatively coupled, one to another.Although not shown, the computing device 1302 may further include asystem bus or other data and command transfer system that couples thevarious components, one to another. A system bus can include any one orcombination of different bus structures, such as a memory bus or memorycontroller, a peripheral bus, a universal serial bus, and/or a processoror local bus that utilizes any of a variety of bus architectures. Avariety of other examples are also contemplated, such as control anddata lines.

The processing system 1304 is representative of functionality to performone or more operations using hardware. Accordingly, the processingsystem 1304 is illustrated as including hardware element 1310 that maybe configured as processors, functional blocks, and so forth. This mayinclude implementation in hardware as an application specific integratedcircuit or other logic device formed using one or more semiconductors.The hardware elements 1310 are not limited by the materials from whichthey are formed or the processing mechanisms employed therein. Forexample, processors may be comprised of semiconductor(s) and/ortransistors (e.g., electronic integrated circuits (ICs)). In such acontext, processor-executable instructions may beelectronically-executable instructions.

The computer-readable storage media 1306 is illustrated as includingmemory/storage 1312. The memory/storage 1312 represents memory/storagecapacity associated with one or more computer-readable media. Thememory/storage component 1312 may include volatile media (such as randomaccess memory (RAM)) and/or nonvolatile media (such as read only memory(ROM), Flash memory, optical disks, magnetic disks, and so forth). Thememory/storage component 1312 may include fixed media (e.g., RAM, ROM, afixed hard drive, and so on) as well as removable media (e.g., Flashmemory, a removable hard drive, an optical disc, and so forth). Thecomputer-readable media 1306 may be configured in a variety of otherways as further described below.

Input/output interface(s) 1308 are representative of functionality toallow a user to enter commands and information to computing device 1302,and also allow information to be presented to the user and/or othercomponents or devices using various input/output devices. Examples ofinput devices include a keyboard, a cursor control device (e.g., amouse), a microphone, a scanner, touch functionality (e.g., capacitiveor other sensors that are configured to detect physical touch), a camera(e.g., which may employ visible or non-visible wavelengths such asinfrared frequencies to recognize movement as gestures that do notinvolve touch), and so forth. Examples of output devices include adisplay device (e.g., a monitor or projector), speakers, a printer, anetwork card, tactile-response device, and so forth. Thus, the computingdevice 1302 may be configured in a variety of ways as further describedbelow to support user interaction.

Various techniques may be described herein in the general context ofsoftware, hardware elements, or program modules. Generally, such modulesinclude routines, programs, objects, elements, components, datastructures, and so forth that perform particular tasks or implementparticular abstract data types. The terms “module,” “functionality,” and“component” as used herein generally represent software, firmware,hardware, or a combination thereof. The features of the techniquesdescribed herein are platform-independent, meaning that the techniquesmay be implemented on a variety of commercial computing platforms havinga variety of processors.

An implementation of the described modules and techniques may be storedon or transmitted across some form of computer-readable media. Thecomputer-readable media may include a variety of media that may beaccessed by the computing device 1302. By way of example, and notlimitation, computer-readable media may include “computer-readablestorage media” and “computer-readable signal media.”

“Computer-readable storage media” may refer to media and/or devices thatenable persistent and/or non-transitory storage of information incontrast to mere signal transmission, carrier waves, or signals per se.Thus, computer-readable storage media refers to non-signal bearingmedia. The computer-readable storage media includes hardware such asvolatile and non-volatile, removable and non-removable media and/orstorage devices implemented in a method or technology suitable forstorage of information such as computer readable instructions, datastructures, program modules, logic elements/circuits, or other data.Examples of computer-readable storage media may include, but are notlimited to, RAM, ROM, EEPROM, flash memory or other memory technology,CD-ROM, digital versatile disks (DVD) or other optical storage, harddisks, magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, or other storage device, tangible media, orarticle of manufacture suitable to store the desired information andwhich may be accessed by a computer.

“Computer-readable signal media” may refer to a signal-bearing mediumthat is configured to transmit instructions to the hardware of thecomputing device 1302, such as via a network. Signal media typically mayembody computer readable instructions, data structures, program modules,or other data in a modulated data signal, such as carrier waves, datasignals, or other transport mechanism. Signal media also include anyinformation delivery media. The term “modulated data signal” means asignal that has one or more of its characteristics set or changed insuch a manner as to encode information in the signal. By way of example,and not limitation, communication media include wired media such as awired network or direct-wired connection, and wireless media such asacoustic, RF, infrared, and other wireless media.

As previously described, hardware elements 1310 and computer-readablemedia 1306 are representative of modules, programmable device logicand/or fixed device logic implemented in a hardware form that may beemployed in some embodiments to implement at least some aspects of thetechniques described herein, such as to perform one or moreinstructions. Hardware may include components of an integrated circuitor on-chip system, an application-specific integrated circuit (ASIC), afield-programmable gate array (FPGA), a complex programmable logicdevice (CPLD), and other implementations in silicon or other hardware.In this context, hardware may operate as a processing device thatperforms program tasks defined by instructions and/or logic embodied bythe hardware as well as a hardware utilized to store instructions forexecution, e.g., the computer-readable storage media describedpreviously.

Combinations of the foregoing may also be employed to implement varioustechniques described herein. Accordingly, software, hardware, orexecutable modules may be implemented as one or more instructions and/orlogic embodied on some form of computer-readable storage media and/or byone or more hardware elements 1310. The computing device 1302 may beconfigured to implement particular instructions and/or functionscorresponding to the software and/or hardware modules. Accordingly,implementation of a module that is executable by the computing device1302 as software may be achieved at least partially in hardware, e.g.,through use of computer-readable storage media and/or hardware elements1310 of the processing system 1304. The instructions and/or functionsmay be executable/operable by one or more articles of manufacture (forexample, one or more computing devices 1302 and/or processing systems1304) to implement techniques, modules, and examples described herein.

The techniques described herein may be supported by variousconfigurations of the computing device 1302 and are not limited to thespecific examples of the techniques described herein. This functionalitymay also be implemented all or in part through use of a distributedsystem, such as over a “cloud” 1313 via a platform 1316 as describedbelow.

The cloud 1314 includes and/or is representative of a platform 1316 forresources 1318. The platform 1316 abstracts underlying functionality ofhardware (e.g., servers) and software resources of the cloud 1314. Theresources 1318 may include applications and/or data that can be utilizedwhile computer processing is executed on servers that are remote fromthe computing device 1302. Resources 1318 can also include servicesprovided over the Internet and/or through a subscriber network, such asa cellular or Wi-Fi network.

The platform 1316 may abstract resources and functions to connect thecomputing device 1302 with other computing devices. The platform 1316may also serve to abstract scaling of resources to provide acorresponding level of scale to encountered demand for the resources1318 that are implemented via the platform 1316. Accordingly, in aninterconnected device embodiment, implementation of functionalitydescribed herein may be distributed throughout the system 1300. Forexample, the functionality may be implemented in part on the computingdevice 1302 as well as via the platform 1316 that abstracts thefunctionality of the cloud 1314.

CONCLUSION

Various implementations described herein are able to leverage theinteraction from one or more potential buyers relative to a digitalimage to automatically create a sales listing for items that appear tobe of interest to the buyers. This reduces or eliminates all togetherthe manual effort previously required of sellers in researching andcollecting data on each item they wish to sell. Because of theirtechnical nature, the innovative solutions described herein are alsoreadily scalable which, in turn, greatly improves the seller'sexperience. Based on buyer interaction experiences, sales listings foreach item for sale can be automatically created and listed.

The described innovations improve upon the current state-of-the-art fora number of different reasons. For example, the described innovationsare extremely helpful and very apt for casual sellers who may notnecessarily be comfortable in, or knowledgeable about identifying itemsthat they can sell. The technical solutions described hereinautomatically take care of all of the details for these types ofsellers. In addition, because of the technical nature of theinnovations, for sellers who do not have the time to manage and list allof the items they wish to sell, the innovative solutions provide a“one-stop” process in which a single digital image can serve as thestarting point for an automatically-created, automatically-listed saleslisting for one or more items. The innovative technical solutions thusemphasize and promote speed, efficiency, and ease of usability forsellers.

Although the invention has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the invention defined in the appended claims is not necessarilylimited to the specific features or acts described. Rather, the specificfeatures and acts are disclosed as example forms of implementing theclaimed invention.

What is claimed is:
 1. A method implemented by a computing device, themethod comprising: monitoring, by the computing device, a userinteraction experience of a user associated with a digital image thatcontains one or more items that are listed via a network-basedexperience, wherein the one or more items have an existing item listingvia the network-based experience; based on the user interactionexperience, developing, by the computing device, item metadata; based onthe item metadata, automatically modifying, by the computing device, theexisting item listing for at least one of the one or more items that arelisted via the network-based experience; and causing, by the computingdevice, the existing item listing as modified to be automatically listedvia the network-based experience.
 2. The method as described in claim 1,wherein the user interaction experience comprises interactions of theuser with the digital image.
 3. The method as described in claim 1,wherein the user interaction experience comprises interactions of theuser with the digital image, and wherein at least one interaction of theuser comprises a zoom operation.
 4. The method as described in claim 1,wherein the user interaction experience comprises an on-line socialinteraction between the user and a listing user of the one or moreitems.
 5. The method as described in claim 1, wherein developing theitem metadata comprises developing the item metadata using one or moremachine learning techniques, acquiring at least some of the itemmetadata from the network-based experience, or acquiring at least someof the item metadata from a source other than the network-basedexperience.
 6. A method implemented by a computing device, the methodcomprising: receiving, by the computing device, data associated with oneor more user interactions with a digital image that contains one or moreitem images of one or more respective items that are listed via anetwork-based experience; processing, by the computing device, the dataassociated with the one or more user interactions to define at least oneregion of interest of the digital image containing one or more items ofinterest; identifying, by the computing device, the one or more items ofinterest contained within the at least one region; responsive toidentifying the one or more items of interest, developing, by thecomputing device, metadata associated with the one or more items ofinterest; using, by the computing device, the developed metadata toautomatically modify an item listing for the one or more items ofinterest; and causing, by the computing device, the item listing asmodified to be automatically listed via the network-based experience. 7.The method as described in claim 6, wherein developing the metadatacomprises developing metadata using one or more machine learningtechniques.
 8. The method as described in claim 6, wherein developingthe metadata comprises acquiring at least some of the metadata from thenetwork-based experience.
 9. The method as described in claim 6, whereindeveloping the metadata comprises acquiring at least some of themetadata from a source other than the network-based experience.
 10. Themethod as described in claim 6, wherein the causing is performed bycausing the item listing as modified to be automatically listed viamultiple different network-based experiences.
 11. The method asdescribed in claim 6, wherein one of the user interactions with thedigital image comprises a zoom operation.
 12. The method as described inclaim 6, wherein: using the developed metadata comprises automaticallymodifying respective item listings for multiple items of interest; andthe causing comprises causing the respective item listings as modifiedto be automatically listed via the network-based experience.
 13. Asystem comprising: one or more processing systems; one or morecomputer-readable storage media storing instructions which, whenexecuted by the one or more processing systems, perform operationscomprising: receiving, by way of a user interface configured to enable alisting user to create an event that can be used to modify at least oneexisting item listing associated with one or more items online, adigital image that contains one or more item images of one or more itemsonline, a digital image that contains one or more item images of one ormore respective items that are associated with the least one existingitem listing to be modified by the listing user as part of the event;enabling, via the user interface, social interaction between the listinguser and one or more other users regarding the one or more respectiveitems appearing in the digital image; monitoring the social interactionbetween the listing user and the one or more other users; developingmetadata based on the monitored social interaction; enabling, based atleast in part on the metadata, modification of the at least one existingitem listing associated with the one or more respective items appearingin the digital image; automatically modifying, based at least in part onthe metadata, the at least one existing item listing of the one or morerespective items appearing in the digital image; and causing, based atleast in part on the at least one existing item listing as modified,updating of the digital image.
 14. The system as described in claim 13,wherein the automatically modifying further comprises automaticallymodifying, based at least in part on the metadata, multiple existingitem listings that contain information associated with the one or morerespective items appearing in the digital image.
 15. The system asdescribed in claim 13, wherein the operations further comprise updatingthe at least one existing item listing as modified responsive tocontinuing to monitor the social interaction.
 16. The system asdescribed in claim 13, wherein the enabling comprises enabling one ofthe other users to buy the one or more items through the socialinteraction.
 17. The system as described in claim 13, wherein theupdating comprises causing display of a visual indicator indicating thatthe at least one existing item listing as modified, of a particularitem, has been modified.
 18. The system as described in claim 13,wherein the updating comprises causing display of a visual indicatorindicating that a particular item is not available.
 19. The system asdescribed in claim 13, wherein the causing further comprises causing theat least one existing item listing as modified to be automaticallylisted via multiple network-based experiences.
 20. The system asdescribed in claim 13, wherein developing the metadata comprisesdeveloping the metadata using one or more machine learning techniques,acquiring at least some of the metadata from the network-basedexperience, or acquiring at least some of the metadata from a sourceother than the network-based experience.